PlayerRank: leveraging learning-to-rank AI for player positioning in cricket by Hassan, Bilal, Clough, Clare, Siddiqi, Yusra, Ali, Rao Faizan, Arshed, Muhammad Asad

“…These models will use listwise ranking algorithms and an artificial neural network architecture to provide data-driven player rankings, enhancing impartiality and performance focus. …”
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​Revisiting soft power : 2019 rankings​ by Gopalan, Sasidaran, Park, Seung Ho

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Separating quantum communication and approximate rank by Anshu, Anurag, Garg, Ankit, Kothari, Robin, Ben-David, Shalev, Jain, Rahul, Lee, Troy

“…All known lower bounds on quantum communication complexity in the general unbounded-round model can be shown via the logarithm of approximate rank, and it was an open problem to give any separation at all between quantum communication complexity and the logarithm of the approximate rank. …”
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Evaluating the merits of ranking in structured network pruning by Sharma, Kuldeep, Ramakrishnan, Nirmala, Prakash, Alok, Lam, Siew-Kei, Srikanthan, Thambipillai

“…In this work, we further explore the value of the ranking criteria in pruning to show that if channels are removed gradually and iteratively, alternating with fine-tuning on the target dataset, ranking criteria are indeed not necessary to select redundant channels. …”
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On the generalised rank weights of quasi-cyclic codes by Lim, Enhui, Oggier, Frédérique

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Webpage ranking: how it affects your selections? by Tan, Pei Li.

“…However, even today‟s most successful search engines struggle to provide high-quality search results: Approximately 50 percent of Web search sessions fail to find any relevant results for the searcher.[1] This project not only helps readers to have a better understanding of how the top 4 search engines works and how they rank their pages but also shows readers method(s) to manipulate the order of displaying results. …”
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Simultaneous object detection and ranking with weak supervision by Blaschko, MB, Vedaldi, A, Zisserman, A

“…To this end we develop a discriminative learning approach and make two contributions: (i) we propose a structured output formulation for weakly annotated images where full annotations are treated as latent variables; and (ii) we propose to optimize a ranking objective function, allowing our method to more effectively use negatively labeled images to improve detection average precision performance. …”

Local universities achieve higher global rankings by Morhan, Sivanisvarry

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Hybrid features ranking with discretization model for writer identification / by Intan Ermahani A. Jalil, 1980- , author 607189, Siti Mariyam Shamsuddin, supervisor 289532, Azah Kamilah Muda, supervisor 621569, Fakulti Kejuruteraan. Sekolah Komputeran 619086

Hybrid features ranking with discretization model for writer identification / by Intan Ermahani A. Jalil, 1980-, author 607189

Impact of Global University Ranking Systems on Developing Countries / by Onyancha, Omwoyo Bosire, editor 656278, Adeyinka, Tella, 1972-, editor 656280, IGI Global (Online service) 631983

“…"The book seeks to offer an opportunity to scholars and other stakeholders from the global south to offer their perspectives on the impact of the global ranking systems on developing countries, and more particularly the global south. …”
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On Generalization Bounds for Neural Networks with Low Rank Layers by Pinto, Andrea, Rangamani, Akshay, Poggio, Tomaso

Subjects: “…Gaussian Complexity, Generalization Bounds, Low Rank Layers, Neural Collapse…”
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Rank weight hierarchy of some classes of polynomial codes by Ducoat, Jérôme, Oggier, Frédérique

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Sparse low-rank matrix approximation for data compression by Hou, Junhui, Chau, Lap-Pui, Magnenat-Thalmann, Nadia, He, Ying

“…Low-rank matrix approximation (LRMA) is a powerful technique for signal processing and pattern analysis. …”
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Ranking of parameters in bioheat transfer using Taguchi analysis by Jamil, Muhammad, Ng, Eddie Yin-Kwee

“…The purpose of this study is to rank the parameters involved in electromagnetic heating and determine the factors which affect the bioheat transfer the most. …”
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Stable Rank-Adaptive Dynamically Orthogonal Runge–Kutta Schemes by Charous, Aaron, Lermusiaux, Pierre F. J.

“…We develop two new sets of stable, rank-adaptive Dynamically Orthogonal Runge-Kutta (DORK) schemes that capture the high-order curvature of the nonlinear low-rank manifold. …”
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Developing an eCommerce Pricing Model Using Rank Centrality by Tong, Kevin C.

“…This paper attempts to model eCommerce competition between different sellers using the principle of Rank Centrality, and uses neural networks to accurately predict the winning seller on eCommerce websites, such as Amazon, based on factors including pricing, seller rating, and shipping guarantees for each seller. …”
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Multifeature Extreme Ordinal Ranking Machine for Facial Age Estimation by Zhao, Wei, Wang, Han, Huang, Guang-Bin

“…To refrain from such algorithm complexity while maintaining a high estimation accuracy, we propose a multifeature extreme ordinal ranking machine (MFEORM) for facial age estimation. …”
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On List-Decodability of Random Rank Metric Codes and Subspace Codes by Ding, Yang

“…Codes in rank metric have a wide range of applications. To construct such codes with better list-decoding performance explicitly, it is of interest to investigate the listdecodability of random rank metric codes. …”
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Laplacian Regularized Subspace Learning for interactive image re-ranking by Zhang, Lining., Wang, Lipo., Lin, Weisi.

“…To bridge the gap between low level visual features and high level semantic concepts, various relevance feedback (RF) or interactive re-ranking (IR) schemes have been designed to improve the performance of a CBIR system. …”
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